MOTIVATION: Standard statistical techniques often assume that data are normally distributed, with constant variance not depending on the mean of the data. Data that violate these assumptions can often be brought in line with the assumptions by application of a transformation. Gene-expression microarray data have a complicated error structure, with a variance that changes with the mean in a non-linear fashion. Log transformations, which are often applied to microarray data, can inflate the variance of observations near background. RESULTS: We introduce a transformation that stabilizes the variance of microarray data across the full range of expression. Simulation studies also suggest that this transformation approximately symmetrizes microarray data.
MOTIVATION: Standard statistical techniques often assume that data are normally distributed, with constant variance not depending on the mean of the data. Data that violate these assumptions can often be brought in line with the assumptions by application of a transformation. Gene-expression microarray data have a complicated error structure, with a variance that changes with the mean in a non-linear fashion. Log transformations, which are often applied to microarray data, can inflate the variance of observations near background. RESULTS: We introduce a transformation that stabilizes the variance of microarray data across the full range of expression. Simulation studies also suggest that this transformation approximately symmetrizes microarray data.
Authors: Kedir N Turi; Jyoti Shankar; Larry J Anderson; Devi Rajan; Kelsey Gaston; Tebeb Gebretsadik; Suman R Das; Cosby Stone; Emma K Larkin; Christian Rosas-Salazar; Steven M Brunwasser; Martin L Moore; R Stokes Peebles; Tina V Hartert Journal: Am J Respir Crit Care Med Date: 2018-10-15 Impact factor: 21.405
Authors: Mina Kalantari-Dehaghi; Sookhee Chun; Aziz Alami Chentoufi; Jozelyn Pablo; Li Liang; Gargi Dasgupta; Douglas M Molina; Algis Jasinskas; Rie Nakajima-Sasaki; Jiin Felgner; Gary Hermanson; Lbachir BenMohamed; Philip L Felgner; D Huw Davies Journal: J Virol Date: 2012-02-08 Impact factor: 5.103